There are several components of the research program. Component 1: Platelet Biology, Reactivity and Genomics. Utilizing one of the largest human samples (FHS: Framingham Heart Study) with platelet reactivity we have conducted deeper genetic scans for contributing genes. These scans use new genetic maps with deeper coverage of rare variation. DNA genotyping of an additional diverse population sample, the FHS OMNI cohort, was supported allowing additional validation samples and gene coverage for platelet reactivity traits. Targeted qPCR RNA measurements in FHS platelet samples are also completed and underway to investigate mechanistic questions for specific candidate genes. Separately, platelet RNA samples were collected from 32 myocardial infarction samples and whole transcriptome RNA sequencing supported to identify genes associated with different factors and diagnoses. Additional cell line and anonymous tissue samples were purchased to augment this work with future RNA sequencing. Component 2: Tissue-specific Gene Expression. A major cell- and tissue-specific database of genetic factors on gene expression (eQTLs) was maintained and updated. This catalog was used to add information on genes to many disease and risk factor studies, primarily in the cardiovascular and metabolic disease domains. In a separate project, gene expression measurements in whole blood samples from >5,300 FHS samples were employed in studies to identify genes whose RNA levels correlated with traits, including new eQTLs. A major study was undertaken to integrate FHS gene expression data with data on 15,000 other samples, leading to the identification and validation of >1,200 genes whose RNA levels change during aging. Research was supported to conduct experiments knocking out some of these novel genes in the worm C. elegans in order to assess whether they significantly affect lifespan. Component 3: Development and Application of Bioinformatics Resources. Beyond the eQTL database mentioned above, a large genome-wide association study (GWAS) results database was updated, and an online NIH query site developed. This database of results from 1,400 GWAS articles was used in research addressing multiple questions including the convergence of GWAS genetic evidence shared in common for cancer and cardiometabolic diseases; convergence of GWAS disease traits on drug targeted genes, suggesting possible novel drug targets or therapeutic re-positionings; and a study on convergence of GWAS findings with tissue-specific eQTL findings. Ongoing updating of the database was supported.